Eugene Ciurana
Eugene Ciurana是一位活跃在旧金山和莫斯科地区的开源贡献者、布道师、企业家。他专注于构建稳健又可扩展的敏捷开发，在诸如Summly、沃尔玛、AT&T、JP Morgan、Oracle、IBM等公司带领团队设计并开发高性能和大数据系统。同时他也在亚洲、东欧、或硅谷帮助很多创业公司打造他们的坚实技术基础。作为雅虎的资深首席工程署，他带领团队为下一代移动和Web应用设计并开发高扩展性语义化Web系统。Eugene经常用/nick pr3d4t0r的IRC代号活跃在#java, #python, #awk, #R, #iphonedev, 和#security等频道。
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主题演讲: Mobile + HA + Cloud = Successful Mobile App HOWTO
How do you go about creating your app, including inception, development, launch, and managing its evolution? This talk will dives into the architectural choices, language selection, mobile target environment, and servers configuration, database, and caching systems that you must consider in making a successful mobile app.
- Very limited budget – making the best out of your funding
- Concepts and design – don't leave anything to chance!
- iOS implementation constraints
- Separation of concerns between mobile and servers
- Balancing processing requirements between mobile and server components
- Programming languages selection
- Dev tools
- A Tale of Many Cities and the distributed dev team: Russia, London, Thailand, Bay Area
- Your value proposition and core technologies
- Integration vs new technology development
- Your technological choices are your best or worst asset
- Implementation of a unique and innovative UI
- Operational model
- Languages: Objective-C, Java, Python, Scala, Android/Java
- Integrating with 3rd-party systems
- Mule Integration Platform
- Databases and your app's future
- mongoDB
- Neo4J
- Others
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演讲主题: Knowledge Discovery and Machine Learning Patterns For Successful Mobile Applications
所属专题:Machine learning and knowledge discovery techniques can be used for building mobile applications that perform well under new situations. Software developers can leverage the network effects of hundreds of thousands of users providing real-time, abundant training sets of usage data to build cost-effective predictive products and services.
- Basics
- Concepts
- Knowledge representation
- Algorithms
- Rules
- Decisions trees
- Instance-based learning
- Clustering
- Evaluation
- The tool set
- System architectures
- Mobile vs cloud separation of concerns
- Programming languages
- Structured vs unstructured data instrumentation
- Toolkits
- System architectures
- Case studies (samples, code, and diagrams)
- Text summarization
- Document and data search
- Urban traffic flows real-time optimization
- Q&A
- Basics